Active-chain-count energy lever sim (#135)#145
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Models the number of active RX chains as an energy lever: each chain adds always-on baseline draw, but combining several improves delivery — so for a fixed video rate the baseline amortises over more delivered bits and less airtime is spent covering losses. Whether the trade pays depends on the antenna correlation rho (fade state), so the energy-optimal chain count adapts to motion, not range. - tools/precoder/chain_count_energy_sim.py (+ pytest): reuses the calibrated power/airtime model (energy_model.py), adds a per-chain baseline and a diversity-improved delivery (outage^N_eff). --self-test and a rho sweep. - docs/adaptive-link.md: "active receive chains" as a fade-state lever. Result: static (high rho) -> optimal N=1 (extra chains pure baseline cost); mobile (low rho) -> optimal N grows, reaching all 4 chains at a deep marginal link. The energy corollary of the measured RX-MRC finding (nil static, pays under motion). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
josephnef
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Summary
The active-chain-count energy lever (#135) — the energy corollary of the measured
RX-MRC finding. A multi-chain receiver can light up 1..N chains; each adds
always-on baseline draw, but combining improves delivery, so for a fixed video
rate the baseline amortises over more delivered bits. Whether the trade pays
depends on the antenna correlation ρ (fade state), so the energy-optimal chain
count adapts to motion, not just range.
Model
Reuses the calibrated power/airtime model (
energy_model.py) and adds:(1-d1)drops to(1-d1)^N_eff, withN_eff = N/(1+(N-1)ρ²)(same metric as the measurementdoc and the space×frequency sim).
Energy per delivered bit
= (P_core + N·P_chain + airtime·P_pa) / (rate · deliver_N).Result (ρ sweep)
optimal N = 1.
more than they cost → optimal N grows, reaching all 4 chains at a deep
marginal link (and shifting up further with cheaper chains).
Contents
tools/precoder/chain_count_energy_sim.py— sim,--sweep/default ρ table,--self-test.tools/precoder/test_chain_count_energy_sim.py— pytest (N_eff, delivery,static→single, mobile→more, marginal→more, cheaper→more).
docs/adaptive-link.md— "active receive chains" as a fade-state lever.Testing
--self-testgreen; 6 pytest pass. Pure-Python, consistent with the sibling sims.🤖 Generated with Claude Code